Videos marked with an (*) contain discussion of new content in ICRFS-Plus™ 12.
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It is important that you study the videos in sequential order as set out below.
4. Modelling real data (CTP) in the PTF modelling framework
4.1 Modelling CTP in PTF manually
In this video, we model the triangle group CTP using the PTF modelling framework. The method of evaluating whether parameters are needed and the method of adding parameters is illustrated. In general, we model development periods first, then whichever direction (accident or calendar) shows the most changes (from left to right).
The methods of modelling: adding trends, detecting outliers, maintaining the normality assumption, and optimisation are covered.
The statistically optimal model has the lowest (Bayes Information Criterion) BIC.
The process of validation is discussed. If the trends in the data are stable, then we expect to find that the model does a well for predicting the most recent years if they are removed from the model estimation. This is shown to be the case for this data.
4.2 Modelling CTP using the Wizard and ELRF
In this video we study the wizard and how it models the triangle group CTP (dataset PL(I)). The wizard is simply a set of commands - similar to a macro. As the wizard builds a model, it evaluates the model structure and, depending on the structure identified, it will consider different alternative models.
In general, the wizard does a good job for modelling data. However, it is always necessary to evaluate a wizard model. That is, you need to determine which wizard model is best, to view outliers, and to check any trends set to zero. If you are not happy with any suggested wizard model, it is always possible to either adjust the wizard model or to build a model manually.
The functionality of PTF as available on the toolbar is also revised.
CTP is briefly examined in the ELRF modelling framework to determine whether ratios have any predictive power.